Goldman Sachs Says Cybersecurity Firms Model Software’s AI Defense

Goldman Sachs is making a more contrarian AI call than the usual software-is-doomed story. Its message is not that software is finished, but that the firms best equipped to survive the AI shock may look a lot like cybersecurity companies: fast-moving, acquisition-ready, and built to defend against relentless change.

Why Goldman is pointing software executives to cybersecurity

The backdrop is a bruising reset in software stocks during the first quarter of 2026. Goldman says that selloff was driven less by a collapse in current business performance than by a sharper argument over the future: pricing power, long-term growth, and whether software companies can keep a moat when agentic AI tools make it easier to build, replace, or repackage products.

That fear is not new inside Goldman’s own research stream. In a March 10 Top of Mind report, the firm said agentic AI tools for software development helped trigger a sharp re-rating of the sector, with investors suddenly wondering whether AI could “eat software.” A February 18 note pushed back on the panic, arguing that the market may be applying AI concerns too broadly and overlooking companies that can use AI to reinforce growth instead of losing share to it.

The tension is important because the valuation reset has been severe. Goldman says that at the recent peak, software names were priced as if medium-term revenue growth would land around 15% to 20%. Under the newer pricing regime, that expectation has fallen to roughly 5% to 10%. That kind of reset changes hiring plans, spend discipline, and acquisition strategy long before it changes reported revenue.

What cybersecurity firms are doing differently

Goldman’s April 23 analysis says U.S. cybersecurity stocks are outperforming the broader U.S. software industry by 24% on enterprise value to forward sales as of April 15, 2026. The point is not that cyber is immune to AI, but that the sector has already learned how to live inside a high-pressure innovation cycle.

Cyber companies face active adversaries, constant product churn, and a market where gaps can become existential quickly. That has forced them to build muscle in two areas that software firms now need more urgently: rapid innovation and fast M&A. If a product gap opens, cyber companies cannot wait for a clean multi-year roadmap. They buy capability, stitch it into the platform, and move on.

For software companies under AI pressure, that is the key lesson Goldman wants the market to absorb. Resilience is no longer just about sticky contracts or installed base. It is about whether a company can adapt product architecture, defend customer trust, and keep widening its offer faster than rivals can commoditize it.

What this means for product teams

For product leaders, Goldman’s framing is a warning against slow-motion roadmaps. If AI lowers the cost of building features, product teams cannot assume that a wide feature set will automatically protect pricing. They need to decide which parts of the stack are defensible, which can be automated, and which should be bundled into a broader platform before customers start unbundling them themselves.

That likely pushes product organizations toward a few priorities:

• Tighten the product gap analysis, especially where AI agents can replicate common workflows quickly.

• Build around workflow control, data advantage, and integration depth rather than surface-level functionality.

• Treat technical debt as a strategic issue, because slower codebases make it harder to respond when AI changes product economics.

• Use selective acquisitions to close missing capabilities faster than internal development would allow.

For employees inside software companies, that translates into more pressure on product managers and engineers to ship faster, but also to make sharper calls. The winners will not be the teams that simply add AI branding to existing tools. They will be the ones that rethink the product from the ground up.

What this means for sales teams

Sales is where the market reset becomes very concrete. If investors are questioning long-term pricing power, customers are probably doing the same in renewal talks. That means sales teams will need to sell durability, not just feature lists. They will be asked to explain why a platform is still worth the price when AI tools can automate pieces of the workflow or make switching easier.

That shifts the conversation from product demos to boardroom concerns. Goldman’s framing suggests clients may increasingly talk about AI as a competitive restructuring force, not just a productivity upgrade. Sales leaders who can connect the product to cost control, risk reduction, and long-term operating leverage will have a better shot at defending renewals and expansion deals.

It also raises the stakes for account coverage. In a market where growth assumptions have already been cut from 15% to 20% down to 5% to 10%, each lost renewal is more damaging because it feeds the thesis that software moats are weakening. For bankers covering these companies, that same pressure may translate into more advisory work around restructurings, tuck-in acquisitions, and strategic reviews.

What this means for talent and culture

The talent implication is just as sharp. Cybersecurity firms have long rewarded people who can move quickly under pressure, and software companies may now need to do the same. That means hiring for adaptability, not just deep specialization, and valuing employees who can work across product, security, and AI implementation rather than staying inside a single functional lane.

It also changes how leadership should think about retention. When the market is re-pricing growth and AI is shifting the operating model, the strongest performers will have more outside options, including exits into better-funded platforms, private markets, or M&A integrations. That matters for compensation planning, because the talent needed to defend a platform during a transition is usually the same talent most likely to be courted elsewhere.

For Goldman employees, the workplace lens is clear. Analysts and associates covering software need to understand that valuation is now tied to defensibility, not just revenue quality. VPs and managing directors need to know that clients will want more than a standard AI narrative. They will want a capital-allocation story, a product strategy, and a hiring plan that can survive a tougher market.

Why M&A and private markets matter more now

Goldman’s broader 2026 M&A outlook reinforces the same logic. The firm says AI is broadening the aperture for strategic dealmaking, while private markets are becoming central to larger and more complex transactions. That matters because the companies most exposed to AI disruption may need to buy capabilities faster than they can build them, and the buyers with the strongest balance sheets will have the best chance to reset their product map before the market punishes them further.

Goldman has also argued that AI could still expand the software opportunity in meaningful ways. In a July 3, 2025 note, Gabriela Borges said customer service software could grow an additional 20% to 45% by 2030 if AI agents boost productivity, application software could reach $780 billion by 2030, and the broader software market’s total addressable market could expand by at least 20%. That keeps this from being a simple death narrative. The bigger point is that the winners will be the firms that can absorb AI, use it to widen their offer, and buy the pieces they do not have.

That is why Goldman’s cybersecurity comparison lands so well. It is not a prediction that software disappears. It is a warning that the next phase of software competition will reward the companies that behave like their most disciplined security peers: always upgrading, always defending, and always ready to buy speed when time matters most.